Abstract
Today interior-point methods of choice for general linear programming are primal-dual infeasible interior-point algorithms. There is a big gap between theoretical algorithms and practical algorithms. Major goals of the project were to narrow the gaps between theory and practice of primal-dual interior-point methods. The PI (principal investigator) played a leading role in joint work with Richard Tapia on constructing the first superlinear and polynomial primal-dual algorithm. PI`s recent work on infeasible interior-point methods established the first polynomial result for today`s interior-point methods of device. More recently, PI established polynomial complexities for Mehrotra-type predictor-corrector methods which have been widely regarded today as the most practically efficient methods. This work has laid a solid theoretical foundation for these methods.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
